Optimising the extrusion process of soap bars and synthetic detergents
Supervisor: Dr Simeon Skopalik and Dr Manlio Tassieri
School: Engineering
Industry Partner: Soapworks Ltd
Description:
Soapworks Ltd are a soap manufacturer based in Easterhouse, Glasgow. They were established by Anita Roddick, founder of the Bodyshop as a social enterprise, and now employ 100 people and supply a broad range of customers from hotel commodity bars to high end prestige brands within the UK, Europe and globally.
Soap bars offer a valuable alternative to liquid soaps and their market is flourishing in response to commitment to The Green Economy and a drive towards sustainable products. The advent of synthetic soap formulations (Syndet) in bar form, opens markets such as shampoo, conditioner and facial bars. However, syndets have proven to be not as easy to manufacture as conventional soaps and their integration with established soap manufacturing plants poses additional challenges. To address these latter, Soapworks Ltd and the team at UofG have designed an action plan for the development of a model to optimise Syndet production, which is based upon the combined expertise of research in Rheology and Computational Fluid Dynamics (CFD). The collaboration between Soapworks Ltd and UofG has been proactive and effective so far, with a first IAA & GKEF pilot project (£27,525) awarded in January 2021 and then an Innovate UK/KTP grant proposal (£232,731) awarded in June 2021. The latter is in progress until April 2024 and has already led to a joint publication in Physics of Fluids, (A rheological characterization of synthetic detergent formulations: Physics of Fluids: Vol 34, No 9).
The aim of this project is to draw the (dimensionless) characteristic curves of two extruders currently employed by Soapworks Ltd for the production of classical soap bars and Syndets. The two extruders are equipped with a monitoring system that stores continuously the process parameters such as temperature, pressure and screw speed. Thus, the opportunity to access a significant amount of valuable data for the development of a simplified analytical model for the identification of the optimal operational production window.